code: def decode_col(self, df, column_name):
      # get columns
      df_en = df[self.column_names_array[column_name]]
  
      # get model
      arr = df_en.to_numpy()
      re_en = self.one_hot_encoder[column_name].inverse_transform(arr)
  
      df2 = pd.DataFrame(re_en)
  
      df2 = df2.rename(columns={0: column_name})
  
      # merge new col to the df
      final_df = df.join(df2)
  
      # remove existing columns
      final_df = final_df.drop(
          self.column_names_array[column_name], axis=1
      )
  
      return final_df
  
file_path: explainx/lib/encode_decode_cat_col.py
imports: from imports import *
  from sklearn.preprocessing import OneHotEncoder
  import numpy
label_desc: Use image node_id 5 for calling the encode_decode_cat_col obj's underlying member method code with example usage: obj.decode_col(df, column_name) and returns: final_df